Compositional kernel learning using tree-based genetic programming for Gaussian process regression

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@Article{jin:2020:SaMO,

• author = "Seung-Seop Jin",
• title = "Compositional kernel learning using tree-based genetic programming for Gaussian process regression",
• journal = "Structural and Multidisciplinary Optimization",
• year = "2020",
• volume = "62",
• number = "3",
• keywords = "genetic algorithms, genetic programming, Gaussian processes regression, Compositional kernel learning, Tree-based genetic programming, Surrogate modeling, Reliability analysis",
• URL = "http://link.springer.com/article/10.1007/s00158-020-02559-7",
• DOI = "doi:10.1007/s00158-020-02559-7",

}

Genetic Programming entries for Seung-Seop Jin

Citations